deck.gl
A GPU-accelerated framework for drawing large data sets as layers on maps and 3D views.
- Stars
- 14.7k
- Forks
- 2.3k
- Licence
- MIT
- Language
- TypeScript
- Last update
- 4 days ago
- Type
- Library
What it is
deck.gl is a visualization framework that uses WebGL2 and WebGPU to draw large data sets quickly in the browser. You feed it an array of data objects, choose layers such as icons, polygons or text, and view them through map, first-person or orthographic views. It is used by developers who need interactive maps and charts over big data, and it also has a Python wrapper called pydeck.
- Plot a large set of geographic points as an interactive map layer
- Draw polygons or icons over a basemap from a data array
- Add picking, highlighting and filtering to a data visualization
- Create a Python-generated map with pydeck
Great for
- Developers building interactive maps or geospatial dashboards over large data sets
- Teams who need GPU rendering for tens of thousands of points or shapes
- Python users who want to produce deck.gl maps through pydeck
- Projects that need custom rendering by extending core classes
Not ideal for
- People wanting a finished tool without coding, since it is a framework for building visualizations
- Simple static charts with small data, where a lighter charting library is easier
- Users on browsers without WebGL2 support, since rendering depends on it
How to get it
- 1
Install with a package manager
You'll need: Node.js for the npm package · Python for pydeck
Install the npm module
npm install deck.glInstall the Python package
pip install pydeck - 2
Run it
- Choose the Pure JS, React, or script tag route from the README
- Follow the linked get-started guide for your chosen route
- Run one of the linked full examples to see a first map render
- Adjust the data and layers to match your own data
- 3
Get the most out of it
- Browse the interactive playground to test layer settings before coding
- Use the API documentation for the latest release when customizing layers
- Extend core classes when built-in layers do not cover your use case
- Check third-party integrations such as the TypeScript typings or Vega bindings listed in the README
Downloads
Strengths
- Built for GPU rendering of large data sets
- Large catalog of tested layers and flexible APIs for customization
- Open-source under the MIT license, part of the OpenJS Foundation's vis.gl project
Trade-offs
- Requires programming knowledge and is not a point-and-click tool
- Relies on WebGL2 or WebGPU support in the user's browser
- The README is truncated here, so detailed setup requirements are not fully confirmed
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| deck.gl (this) | 14.7k | Library | intermediate | 4 days ago | Developers building interactive maps or geospatial dashboards over large data sets |
| kepler.gl | 12.1k | Library | intermediate | 4 days ago | Developers who want to add map-based data exploration to a React and Redux app |
| plotly.js | 18.4k | Library | beginner | 7 days ago | Web developers who want interactive charts in their own site or app |
| visx | 21.1k | Library | intermediate | 5 months ago | React developers who want full control over how a chart looks and behaves |
| plotly.py | 18.9k | Library | beginner | 5 days ago | Python users who want hoverable, zoomable charts without writing JavaScript |
| G2 | 12.7k | Library | intermediate | 9 days ago | Front-end developers adding charts to a web dashboard |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.